运行火花3.2的ServiceConfigurationError

Question

我正在尝试更新使用 spark 2.4 编写的代码并使用 spark 3.2 进行一些测试。我能够创建一个火花会话：

spark = (
    SparkSession.builder
        .config('spark.jars.packages', 'org.apache.hadoop:hadoop-azure:3.2.0,com.crealytics:spark-excel_2.11:0.13.1')
        .config('spark.hadoop.fs.azure', "org.apache.hadoop.fs.azure.NativeAzureFileSystem")
        .config("spark.hadoop.fs.azure.account.key." + storage_account + ".blob.core.windows.net", storage_account_key)
        .config("spark.driver.memory", "32G")
        .master("local[*]")
        .appName("Dev")
        .getOrCreate()
)
spark.sparkContext._jsc.hadoopConfiguration().set("fs.wasbs.impl", "org.apache.hadoop.fs.azure.NativeAzureFileSystem")

但是当我尝试用

阅读一些东西时

spark.read.parquet(some_parquet_somewhere)

我收到以下错误：

Py4JJavaError: An error occurred while calling o104.parquet.
: java.util.ServiceConfigurationError: org.apache.spark.sql.sources.DataSourceRegister: Provider org.apache.spark.sql.delta.sources.DeltaDataSource could not be instantiated
    at java.util.ServiceLoader.fail(ServiceLoader.java:232)
    at java.util.ServiceLoader.access$100(ServiceLoader.java:185)
    at java.util.ServiceLoader$LazyIterator.nextService(ServiceLoader.java:384)
    at java.util.ServiceLoader$LazyIterator.next(ServiceLoader.java:404)
    at java.util.ServiceLoader$1.next(ServiceLoader.java:480)
    at scala.collection.convert.Wrappers$JIteratorWrapper.next(Wrappers.scala:46)
    at scala.collection.Iterator.foreach(Iterator.scala:943)
    at scala.collection.Iterator.foreach$(Iterator.scala:943)
    at scala.collection.AbstractIterator.foreach(Iterator.scala:1431)
    at scala.collection.IterableLike.foreach(IterableLike.scala:74)
    at scala.collection.IterableLike.foreach$(IterableLike.scala:73)
    at scala.collection.AbstractIterable.foreach(Iterable.scala:56)
    at scala.collection.TraversableLike.filterImpl(TraversableLike.scala:303)
    at scala.collection.TraversableLike.filterImpl$(TraversableLike.scala:297)
    at scala.collection.AbstractTraversable.filterImpl(Traversable.scala:108)
    at scala.collection.TraversableLike.filter(TraversableLike.scala:395)
    at scala.collection.TraversableLike.filter$(TraversableLike.scala:395)
    at scala.collection.AbstractTraversable.filter(Traversable.scala:108)
    at org.apache.spark.sql.execution.datasources.DataSource$.lookupDataSource(DataSource.scala:652)
    at org.apache.spark.sql.execution.datasources.DataSource$.lookupDataSourceV2(DataSource.scala:720)
    at org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:210)
    at org.apache.spark.sql.DataFrameReader.parquet(DataFrameReader.scala:596)
    at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
    at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
    at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
    at java.lang.reflect.Method.invoke(Method.java:498)
    at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)
    at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
    at py4j.Gateway.invoke(Gateway.java:282)
    at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
    at py4j.commands.CallCommand.execute(CallCommand.java:79)
    at py4j.ClientServerConnection.waitForCommands(ClientServerConnection.java:182)
    at py4j.ClientServerConnection.run(ClientServerConnection.java:106)
    at java.lang.Thread.run(Thread.java:748)
Caused by: java.lang.NoClassDefFoundError: org/apache/spark/internal/Logging$class
    at org.apache.spark.sql.delta.sources.DeltaDataSource.<init>(DeltaDataSource.scala:43)
    at sun.reflect.NativeConstructorAccessorImpl.newInstance0(Native Method)
    at sun.reflect.NativeConstructorAccessorImpl.newInstance(NativeConstructorAccessorImpl.java:62)
    at sun.reflect.DelegatingConstructorAccessorImpl.newInstance(DelegatingConstructorAccessorImpl.java:45)
    at java.lang.reflect.Constructor.newInstance(Constructor.java:423)
    at java.lang.Class.newInstance(Class.java:442)
    at java.util.ServiceLoader$LazyIterator.nextService(ServiceLoader.java:380)
    ... 31 more

我知道这是一个配置问题，但我不确定是哪一个。我真的很感激一些帮助

编辑：我尝试在 Jupyter Notebook 中使用 pyspark 时遇到这些错误，我尝试在控制台中使用 pyspark 并且从 Azure Blob 存储读取没有问题。

因为我收到了这条消息：

/opt/spark/python/pyspark/sql/readwriter.py in parquet(self, *paths, **options)
299                        int96RebaseMode=int96RebaseMode)
300 
--> 301         return self._df(self._jreader.parquet(_to_seq(self._spark._sc, paths)))
    302 
    303     def text(self, paths, wholetext=False, lineSep=None, pathGlobFilter=None,

~/.pyenv/versions/3.7.3/lib/python3.7/site-packages/py4j/java_gateway.py in __call__(self, *args)
   1320         answer = self.gateway_client.send_command(command)
   1321         return_value = get_return_value(
-> 1322             answer, self.gateway_client, self.target_id, self.name)
   1323 
   1324         for temp_arg in temp_args:

/opt/spark/python/pyspark/sql/utils.py in deco(*a, **kw)
    109     def deco(*a, **kw):
    110         try:
--> 111             return f(*a, **kw)
    112         except py4j.protocol.Py4JJavaError as e:
    113             converted = convert_exception(e.java_exception)

~/.pyenv/versions/3.7.3/lib/python3.7/site-packages/py4j/protocol.py in get_return_value(answer, gateway_client, target_id, name)
    326                 raise Py4JJavaError(
    327                     "An error occurred while calling {0}{1}{2}.\n".
--> 328                     format(target_id, ".", name), value)
    329             else:
    330                 raise Py4JError(

我认为可能是环境变量有问题，所以我尝试使用

export SPARK_HOME=spark/installation/folder

和

import findspark
findspark.init()

无济于事。

Answer 1

好吧，就像 OneCricketeer 提到的问题是 Delta Lake 版本。运行：

pyspark --packages io.delta:delta-core_2.12:1.1.0 --conf "spark.sql.extensions=io.delta.sql.DeltaSparkSessionExtension" --conf "spark.sql.catalog.spark_catalog=org.apache.spark.sql.delta.catalog.DeltaCatalog"

解决了